Hi, again, Just a small note, the "fit3" in ordinary.t is simply a error from my side. It should be: ordinary.t <- fit$coef / fit$stdev.unscaled / fit$sigma This does not change the way ordinary.t behaves. Best, Boel Thank you Al. > > > -----Original Message----- > > From: bioconductor-bounces at stat.math.ethz.ch > > [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of > > Boel Brynedal > > Sent: 25 July 2008 12:19 > > To: bioconductor at stat.math.ethz.ch > > Subject: [BioC] Link to picture: Comparison of diff. > > t-statistics, Limma and rowttests > > > > > > Dear List, > > > > Thank you (Wolfgang and Paolo) for telling me the attachment > > did not get through. This is a link to the picture: > > http://picasaweb.google.se/Boelbubblan/Statistics/photo > > > > Cheers, > > Boel > > > > --~*~**~***~*~***~**~*~-- > > Boel Brynedal, MSc, PhD student > > Karolinska Institutet > > Department of Clinical neuroscience > > > > > > ----- Original Message ----- > > From: Boel Brynedal <boel.brynedal at="" ki.se=""> > > Date: Friday, July 25, 2008 9:33 am > > Subject: Comparison of diff. t-statistics, Limma and rowttests > > To: bioconductor at stat.math.ethz.ch > > > > > Dear List, > > > > > > I have affy hgu133plus2 arrays from individuals with > > disease, in two > > > different stages of the disease. I've earlier used > > rowttests and FDR > > > correction. Now I was playing around with limma to see what > > I could do > > > (added different covariates etc) but also investigated the > > most simple > > > setting, comparing the two different stages directly using > > Limma. The > > > first thing that struck me was that limma "finds" only half > > the amount > > > of significantly diff expressed genes. So I started to look at > the > > > t-statistics from limma. Then I stumbled across this: when I do > a > > > qq-plot of the ordinary t-statistics they are far from normally > > > distributed, and actually totally strange. See attached > > plot comparing > > > the ordinary t, the moderate t (both from Limma) as well as t- > > > statisticsfrom rowttests ("Diff_tStatistics_Limma.jpg"). > > > > > > Am I doing something completely wrong? The assumption of equal > > > variancetaken using ordinary t could not create this, could it? > > > Please help me > > > figure out what's wrong here, I'm hoping I've done some stupid > > > mistake.What else could explain this? Thank you. > > > > > > Best wishes, > > > Boel > > > > > > My code and sessionInfo: > > > > > > # eset is a filtered, gcrma normalized ExpressionSet with ~10 000 > > > probesets, 24 arrays. > > > library(limma) > > > library(Biobase) > > > library(genefilter) > > > specific<-factor(c(rep("stageA",10),rep("stageB",14)), > > > levels=c("stageB","stageA")) > > > design<-model.matrix(~specific) > > > fit<-lmFit(eset,design) > > > Fit<-eBayes(fit) > > > > > > ordinary.t <- fit3$coef / fit3$stdev.unscaled / fit3$sigma > > > moderate.t<-Fit$t[,2] > > > rowttests.t<-rowttests(eset,fac=specific) > > > > > > par(mfrow=c(1,3)) > > > qqnorm(ordinary.t,main="fit ordinary.t") > > > qqnorm(moderate.t, main=" Fit moderate.t") > qqnorm(rowttests.t[,1], > > > main= "rowttests.t") > > > dev2bitmap("Diff_tStatistics_Limma.jpg",type="jpeg", height > > = 5, width > > > = 15, res = 75) > > > > > > > sessionInfo() > > > R version 2.7.1 (2008-06-23) > > > x86_64-unknown-linux-gnu > > > > > > locale: > > > ... > > > > > > attached base packages: > > > [1] splines tools stats graphics grDevices utils > > > datasets[8] methods base > > > > > > other attached packages: > > > [1] genefilter_1.20.0 survival_2.34-1 Biobase_2.0.1 > > limma_2.14.5 > > > > > > loaded via a namespace (and not attached): > > > [1] annotate_1.18.0 AnnotationDbi_1.2.2 DBI_0.2-4 > > > [4] RSQLite_0.6-9 > > > > > > --~*~**~***~*~***~**~*~-- > > > Boel Brynedal, MSc, PhD student > > > Karolinska Institutet > > > Department of Clinical neuroscience > > > > > > > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor at stat.math.ethz.ch > > https://stat.ethz.ch/mailman/listinfo/biocondu> ctor > > Search the > > archives: > > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > > > > -- > The Wellcome Trust Sanger Institute is operated by Genome Research > Limited, a charity registered in England with number 1021457 and a > company registered in England with number 2742969, whose > registered > office is 215 Euston Road, London, NW1 2BE. >